I am a PhD-qualified Biomedical Engineer and Biomechanics Expert with a strong interdisciplinary background spanning physics, engineering, and data science. My career is distinguished by advanced expertise in data analysis, mathematical modelling, and signal processing, underpinned by proficiency in Python, MATLAB/Simulink, and SPSS. I have a proven record of applying data-driven and modelling approaches to address real-world challenges, particularly in the development and optimisation of neuroprosthetic devices and biomechanical systems.
Key Achievements
Enhanced neuroprosthetic design by implementing physics-informed neural networks, significantly improving the predictive accuracy of joint kinematics.
Led the PROLIMB project workshop, overseeing all aspects of planning, scheduling, and participant engagement in a multidisciplinary research environment.
Awarded first place for both Best PhD Oral and Poster Presentations at leading UK biomedical engineering conferences.
Secured an EPSRC-funded scholarship in recognition of research excellence and contribution to advancing knowledge in sustainable and resilient engineering.
Delivered technical training and project supervision in engineering and technical modules, including MATLAB/Simulink, PID controllers, and electrical engineering concepts, fostering independent learning and technical competence among students.
Founded and led an Automation Engineering Club, spearheading Arduino-based projects addressing practical challenges and providing technical mentorship.
Consistently presented research findings at national and international conferences, collaborating with leading institutions such as UCL and UHCW.
These achievements reflect my commitment to innovation, effective collaboration, and the practical application of advanced engineering and data science techniques to solve complex problems across diverse domains.More...